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            "creatorSummary": "Jelínek and Peter Wagner",
            "parsedDate": "2007",
            "numChildren": 0
        },
        "data": {
            "key": "JG5ABZTK",
            "version": 1,
            "itemType": "journalArticle",
            "title": "Landslide hazard zonation by deterministic analysis",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "Róbert",
                    "lastName": "Jelínek"
                },
                {
                    "creatorType": "author",
                    "name": "Peter Wagner"
                }
            ],
            "abstractNote": "A practical application of a simple and economical solution\nto landslide hazard zonation based on slope stability analysis was\ncarried out in the Veľká Čausa landslide, Horná Nitra region, central\nSlovakia. The region is prone to different types of slope deformation\ncontrolled by geological structure, physical and mechanical properties\nof materials, complicated hydrogeological setting, undulating morphology,\nandman-made influence. Taking into consideration the cause\nof the landslide, identified as groundwater change, two scenarios of\nlandslide activity have been investigated. Scenario 1 considers the\nmaximum groundwater level recorded from March 1995 to October\n1998, corresponding to the period starting from the most recent\nlandslide activity up to the end of remediation work. Scenario 2\nconsiders the maximum groundwater level recorded from November\n1998 to December 2004, after the remediation works, and corresponding\nto the actual situation of the landslide. It has been found from this\nstudy that slope angle has the highest influence on landslide instability\nin the Veľká Čausa landslide. Therefore, high resolution Digital\nElevationModel (DEM) is essential for obtaining reasonable results. In\naddition, an appropriate selection of the model input parameters (e.g.,\nshear strength) is very important. The validation between the\ncalculated landslide hazard zonation map and results of monitoring\nsurvey were examined. The results show moderate to good agreement\nwith the inclinometric and geodeticmeasurements. It was also verified\nthat the most active part of the landslide is the north-western side",
            "publicationTitle": "Landslides",
            "publisher": "",
            "place": "",
            "date": "2007",
            "volume": "4",
            "issue": "",
            "section": "",
            "partNumber": "",
            "partTitle": "",
            "pages": "339-350",
            "series": "",
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            "dateAdded": "2011-08-25T14:47:27Z",
            "dateModified": "2011-08-25T14:49:27Z"
        }
    },
    {
        "key": "DEVR5C29",
        "version": 1,
        "library": {
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            "name": "landslide risk",
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            },
            "creatorSummary": "Dai et al.",
            "parsedDate": "2002",
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        },
        "data": {
            "key": "DEVR5C29",
            "version": 1,
            "itemType": "journalArticle",
            "title": "Landslide risk assessment and management: an overview",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "F.C.",
                    "lastName": "Dai"
                },
                {
                    "creatorType": "author",
                    "firstName": "C.F.",
                    "lastName": "Lee"
                },
                {
                    "creatorType": "author",
                    "firstName": "Y.Y.",
                    "lastName": "Ngai"
                }
            ],
            "abstractNote": "Landslides can result in enormous casualties and huge economic losses in mountainous regions. In order to mitigate\nlandslide hazard effectively, new methodologies are required to develop a better understanding of landslide hazard and to make\nrational decisions on the allocation of funds for management of landslide risk. Recent advances in risk analysis and risk\nassessment are beginning to provide systematic and rigorous processes to enhance slope management. In recent years, risk\nanalysis and assessment has become an important tool in addressing uncertainty inherent in landslide hazards. This article\nreviews recent advances in landslide risk assessment and management, and discusses the applicability of a variety of approaches\nto assessing landslide risk. Firstly, a framework for landslide risk assessment and management by which landslide risk can be\nreduced is proposed. This is followed by a critical review of the current state of research on assessing the probability of\nlandsliding, runout behavior, and vulnerability. Effective management strategies for reducing economic and social losses due to\nlandslides are described. Problems in landslide risk assessment and management are also examined. D 2002 Elsevier Science\nB.V. All rights reserved.",
            "publicationTitle": "Engineering Geology",
            "publisher": "",
            "place": "",
            "date": "2002",
            "volume": "64",
            "issue": "",
            "section": "",
            "partNumber": "",
            "partTitle": "",
            "pages": "65–87",
            "series": "",
            "seriesTitle": "",
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            "dateAdded": "2011-08-25T14:44:41Z",
            "dateModified": "2011-08-25T14:47:22Z"
        }
    },
    {
        "key": "4U3UTVDK",
        "version": 1,
        "library": {
            "type": "group",
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            "name": "landslide risk",
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            "creatorSummary": "Peduzzi",
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            "version": 1,
            "itemType": "journalArticle",
            "title": "Landslides and vegetation cover in the 2005 North Pakistan\nearthquake: a GIS and statistical quantitative approach",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "P.",
                    "lastName": "Peduzzi"
                }
            ],
            "abstractNote": "The growing concern for loss of services once\nprovided by natural ecosystems is getting increasing attention.\nHowever, the accelerating rate of natural resources destruction\ncalls for rapid and global action. With often very\nlimited budgets, environmental agencies and NGOs need\ncost-efficient ways to quickly convince decision-makers that\nsound management of natural resources can help to protect\nhuman lives and their welfare. The methodology described\nin this paper, is based on geospatial and statistical analysis,\ninvolving simple Geographical Information System (GIS)\nand remote sensing algorithms. It is based on free or very\nlow-cost data. It aims to scientifically assess the potential\nrole of vegetation in mitigating landslides triggered by earthquakes\nby normalising for other factors such as slopes and\ndistance from active fault. The methodology was applied to\nthe 2005 North Pakistan/India earthquake which generated\na large number of victims and hundreds of landslides. The\nstudy shows that if slopes and proximity from active fault are\nthe main susceptibility factors for post landslides triggered\nby earthquakes in this area, the results clearly revealed that\nareas covered by denser vegetation suffered less and smaller\nlandslides than areas with thinner (or devoid of) vegetation\ncover. Short distance from roads/trails and rivers also proved\nto be pertinent factors in increasing landslides susceptibility.\nThis project is a component of a wider initiative involving\nthe Global Resource Information Database Europe from the\nUnited Nations Environment Programme, the International\nUnion for Conservation of Nature, the Institute of Geomatics\nand Risk Analysis from the University of Lausanne and the\n“institut universitaire d’´etudes du d´eveloppement” from the\nUniversity of Geneva",
            "publicationTitle": "Natural Hazards and Earth System Sciences",
            "publisher": "",
            "place": "",
            "date": "",
            "volume": "10",
            "issue": "623-640",
            "section": "",
            "partNumber": "",
            "partTitle": "",
            "pages": "2010",
            "series": "",
            "seriesTitle": "",
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            "dateAdded": "2011-08-25T14:43:11Z",
            "dateModified": "2011-08-25T14:44:28Z"
        }
    },
    {
        "key": "HAG3JWXA",
        "version": 1,
        "library": {
            "type": "group",
            "id": 51104,
            "name": "landslide risk",
            "links": {
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        "meta": {
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            },
            "creatorSummary": "Kirschbaum",
            "parsedDate": "2009",
            "numChildren": 0
        },
        "data": {
            "key": "HAG3JWXA",
            "version": 1,
            "itemType": "manuscript",
            "title": "MULTI-SCALE LANDSLIDE HAZARD AND RISK ASSESSMENT:\nA MODELING AND MULTIVARIATE STATISTICAL APPROACH",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "Dalia Bach",
                    "lastName": "Kirschbaum"
                }
            ],
            "abstractNote": "Landslide susceptibility and hazard assessments in common use are applied to small\nregions, where high-resolution, in situ, observables are available. When approximated\nover larger areas, these analyses are often restricted by the absence of landslide\ninventories, complex or data-intensive methodologies, and surface observable data\nresolution and availability. As a result, few analyses have considered how landslide\nhazard assessment can be approximated and modeled at regional and global scales. The\nincreasing availability of remotely sensed surface data and precipitation products presents\nthe opportunity to explore how these small-scale investigations may be scaled up to\nlarger areas. In this thesis, I seek to bridge the gap between site-specific and global\nlandslide susceptibility, hazard and risk assessments by identifying potential modeling\napproaches and surface observable data that can be transferable over a variety of spatial\nscales. A preliminary satellite-based global algorithm provides the framework in which to\nevaluate how the landslide susceptibility and satellite derived rainfall estimates can\nforecast potential landslide conditions globally. An analysis of this algorithm using a\nnewly developed global landslide inventory dataset suggests that forecasting errors are\ngeographically variable due to improper weighting of surface observables, resolution of\nthe current susceptibility map, and limitations in the availability of landslide inventory\ndata. These methodological and data limitation issues can be more thoroughly assessed at the regional level, where I develop a new susceptibility map using pre-existing regional\nlandslide inventory data and higher resolution surface observables. These analyses\nexplore the scaling relationships and transferability of two methodologies and several\nsurface data products from local to regional scales and indicate that simple bivariate\nmodeling techniques can more effectively approximate susceptibility at regional scales\ncompared to more popular and complex modeling methodologies. Data availability and\nresolution, particularly for geomorphologic information, landslide inventories, and\nrainfall extremes, remain limiting factors in affecting the accuracy of landslide\nsusceptibility assessments at multiple spatial scales. However, this thesis provides\nevidence that integrating available surface observable and precipitation products can\ngreatly enhance landslide susceptibility, hazard and risk assessments and provide the\nfoundation for improving dynamic landslide hazard forecasting in the future.",
            "manuscriptType": "Dissertation",
            "institution": "",
            "place": "COLUMBIA UNIVERSITY",
            "date": "2009",
            "numPages": "210",
            "number": "",
            "DOI": "",
            "citationKey": "",
            "url": "",
            "accessDate": "",
            "archive": "",
            "archiveLocation": "",
            "shortTitle": "",
            "language": "English",
            "libraryCatalog": "",
            "callNumber": "",
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            "relations": {},
            "dateAdded": "2011-08-25T14:40:03Z",
            "dateModified": "2011-08-25T14:42:24Z"
        }
    },
    {
        "key": "XCZZKT9V",
        "version": 1,
        "library": {
            "type": "group",
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            "name": "landslide risk",
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            },
            "creatorSummary": "Chowdhury and Flentje",
            "parsedDate": "2002",
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        },
        "data": {
            "key": "XCZZKT9V",
            "version": 1,
            "itemType": "journalArticle",
            "title": "Role of slope reliability analysis\nin landslide risk management",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "R.",
                    "lastName": "Chowdhury"
                },
                {
                    "creatorType": "author",
                    "firstName": "P.",
                    "lastName": "Flentje"
                }
            ],
            "abstractNote": "Progress in the use of qualitative and\nquantitative methods of landslide risk assessment is\nbriefly reviewed. The use of a hazard-consequence\nmatrix approach is highlighted and attention is then\nrestricted to aspects of hazard assessment in which\nformal reliability concepts can be used. Widely accepted\ngeotechnical and geological models must\nform the basis of credible hazard assessments under\ndifferent environmental conditions. However, conventional\ndeterministic methods of geotechnical\nanalysis need to be supplemented by studies within a\nprobabilistic framework which takes into consideration\nparameter variability and other uncertainties. Suggestions are made for using the ‘‘reliability index’’ in preference to the ‘‘factor of safety’’in comprehensive procedures for landslide risk\nmanagement.",
            "publicationTitle": "Bulletin of Engineering Geology and the Environment",
            "publisher": "",
            "place": "",
            "date": "2002",
            "volume": "62",
            "issue": "",
            "section": "",
            "partNumber": "",
            "partTitle": "",
            "pages": "41-46",
            "series": "",
            "seriesTitle": "",
            "seriesText": "",
            "journalAbbreviation": "",
            "DOI": "",
            "citationKey": "",
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            "tags": [],
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            "relations": {},
            "dateAdded": "2011-08-25T14:35:54Z",
            "dateModified": "2011-08-25T14:39:01Z"
        }
    },
    {
        "key": "GIM6EHN9",
        "version": 1,
        "library": {
            "type": "group",
            "id": 51104,
            "name": "landslide risk",
            "links": {
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            },
            "creatorSummary": "Devoli et al.",
            "parsedDate": "2009",
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        },
        "data": {
            "key": "GIM6EHN9",
            "version": 1,
            "itemType": "journalArticle",
            "title": "Statistical Analysis of Landslide Events in Central America\nand their Run-out Distance",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "Graziella",
                    "lastName": "Devoli"
                },
                {
                    "creatorType": "author",
                    "firstName": "Fabio V.",
                    "lastName": "De Blasio"
                },
                {
                    "creatorType": "author",
                    "firstName": "Anders",
                    "lastName": "Elverhøi"
                }
            ],
            "abstractNote": "Statistical analyses of landslide deposits\nfrom similar areas provide information on dynamics\nand rheology, and are the basis for empirical relationships\nfor the prediction of future events. In Central\nAmerica landslides represent an important threat in\nboth volcanic and non-volcanic areas. Data, mainly\nfrom 348 landslides in Nicaragua, and 19 in other\nCentral American countries have been analyzed to\ndescribe landslide characteristics and to search for\npossible correlations and empirical relationships. The\nmobility of a landslide, expressed as the ratio between\nheight of fall (H) and run-out distance (L) as a function\nof the volume and height of fall; and the relationship\nbetween the height of fall and run-out distance were\nstudied for rock falls, slides, debris flows and debris\navalanches. The data show differences in run-out\ndistance and landslide mobility among different types\nof landslides and between debris flows in volcanic and\nnon-volcanic areas. The new Central American data\nadd to and seem consistent with data published from\nother regions. Studies combining field observations\nand empirical relationships with laboratory studies and\nnumerical simulations will help in the development of\nmore reliable empirical equations for the prediction of\nlandslide run-out, with applications to hazard zonation\nand design of optimal risk mitigation measures.",
            "publicationTitle": "Geotechnical and Geological Engineering",
            "publisher": "",
            "place": "",
            "date": "2009",
            "volume": "27",
            "issue": "",
            "section": "",
            "partNumber": "",
            "partTitle": "",
            "pages": "23-42",
            "series": "",
            "seriesTitle": "",
            "seriesText": "",
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            "dateAdded": "2011-08-25T14:32:39Z",
            "dateModified": "2011-08-25T14:35:55Z"
        }
    },
    {
        "key": "W7HD4WGF",
        "version": 1,
        "library": {
            "type": "group",
            "id": 51104,
            "name": "landslide risk",
            "links": {
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        },
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                "href": "https://api.zotero.org/groups/51104/items/W7HD4WGF",
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                }
            },
            "creatorSummary": "Davis et al.",
            "parsedDate": "2006",
            "numChildren": 0
        },
        "data": {
            "key": "W7HD4WGF",
            "version": 1,
            "itemType": "journalArticle",
            "title": "Two models for evaluating landslide hazards",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "John C.",
                    "lastName": "Davis"
                },
                {
                    "creatorType": "author",
                    "firstName": "Chang-Jo",
                    "lastName": "Chung"
                },
                {
                    "creatorType": "author",
                    "firstName": "Gregory C.",
                    "lastName": "Ohlmacher"
                }
            ],
            "abstractNote": "Two alternative procedures for estimating landslide hazards were evaluated using data on topographic digital elevation\nmodels (DEMs) and bedrock lithologies in an area adjacent to the Missouri River in Atchison County, Kansas, USA. The\ntwo procedures are based on the likelihood ratio model but utilize different assumptions. The empirical likelihood ratio\nmodel is based on non-parametric empirical univariate frequency distribution functions under an assumption of\nconditional independence while the multivariate logistic discriminant model assumes that likelihood ratios can be\nexpressed in terms of logistic functions.\nThe relative hazards of occurrence of landslides were estimated by an empirical likelihood ratio model and by\nmultivariate logistic discriminant analysis. Predictor variables consisted of grids containing topographic elevations, slope\nangles, and slope aspects calculated from a 30-m DEM. An integer grid of coded bedrock lithologies taken from digitized\ngeologic maps was also used as a predictor variable. Both statistical models yield relative estimates in the form of the\nproportion of total map area predicted to already contain or to be the site of future landslides. The stabilities of estimates\nwere checked by cross-validation of results from random subsamples, using each of the two procedures. Cell-by-cell\ncomparisons of hazard maps made by the two models show that the two sets of estimates are virtually identical. This\nsuggests that the empirical likelihood ratio and the logistic discriminant analysis models are robust with respect to the\nconditional independent assumption and the logistic function assumption, respectively, and that either model can be used\nsuccessfully to evaluate landslide hazards",
            "publicationTitle": "Computers and Geoscience",
            "publisher": "",
            "place": "",
            "date": "2006",
            "volume": "32",
            "issue": "",
            "section": "",
            "partNumber": "",
            "partTitle": "",
            "pages": "1120–1127",
            "series": "",
            "seriesTitle": "",
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            "relations": {},
            "dateAdded": "2011-08-25T14:29:53Z",
            "dateModified": "2011-08-25T14:32:24Z"
        }
    },
    {
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            "title": "Slope stability evaluation using Back Propagation Neural Networks",
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                    "firstName": "H.B.",
                    "lastName": "Wang"
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            "abstractNote": "The Yudonghe landslide, located in western Hubei Province of China, consists of eastern and western subunits as well as a\nmain landslide mass with upper and lower slip surfaces. As an important landslide close to Shuibuya Dam on the Qing River, its\nstability is crucial, as the slide might reactivate because of a change in ground-water level caused by filling of the Shuibuya\nReservoir. Existing weakness zones, growth of ruptures, the downslope attitude of geologic strata, and water infiltration, which\nreduced the strength of rocks and soils, have been found to be the most important factors contributing to the Yudonghe\nlandslide. With regard to the landslide processes, it can be noted that the original large-scale slide activity was due to erosion by\nthe Qing River, the second sliding resulted from the fall of blocks from the head scarp, and the final activity was the growth of\nthe eastern and western secondary slides. A base failure was the main type of slope movement, however, it was obvious that\nmore than one sliding event occurred, as inferred from striations and fractures detected by microstructure analysis of soils along\nthe failure surfaces. Slope instability was evaluated by the method of Back Propagation Neural Networks (BPNN), in which a\nfour-layer BPNN model with five input nodes, two hidden layers, and two output nodes was constructed using a training data\nset of landslide samples throughout the Qing River area. The predicted results of this analysis showed that the factor of safetywas 1.10, which indicates that the Yudonghe landslide is currently in a marginally stable condition.\nD 2005 Elsevier B.V. All rights reserved.",
            "publicationTitle": "Engineering Geology",
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            "title": "Neural network modeling applications in active slope stability\nproblems",
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                    "firstName": "Rennie B.",
                    "lastName": "Kaunda"
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                {
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                    "lastName": "Chase"
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            "abstractNote": "A back propagation artificial neural network\napproach is applied to three common challenges in engineering\ngeology: (1) characterization of subsurface geometry/\nposition of the slip (or failure surface) of active\nlandslides, (2) assessment of slope displacements based on\nground water elevation and climate, and (3) assessment of\ngroundwater elevations based on climate data. Series of\nneural network models are trained, validated, and applied\nto a landslide study along Lake Michigan and cases from\nthe literature. The subsurface characterization results are\nalso compared to a limit equilibrium circular failure surface\nsearch with specific adopted boundary conditions. It is\ndetermined that the neural network models predict slip\nsurfaces better than the limit equilibrium slip surface\nsearch using the most conservative criteria. Displacements\nand groundwater elevations are also predicted fairly well,\nin real time. The models’ ability to predict displacements\nand groundwater elevations provides a foundational\nframework for building future warning systems with\nadditional inputs.",
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            "abstractNote": "The scope of this teaching package is to make a brief induction to Artificial Neural\nNetworks (ANNs) for people who have no previous knowledge of them. We first make a brief\nintroduction to models of networks, for then describing in general terms ANNs. As an\napplication, we explain the backpropagation algorithm, since it is widely used and many other\nalgorithms are derived from it.\nThe user should know algebra and the handling of functions and vectors. Differential\ncalculus is recommendable, but not necessary. The contents of this package should be\nunderstood by people with high school education. It would be useful for people who are just\ncurious about what are ANNs, or for people who want to become familiar with them, so when\nthey study them more fully, they will already have clear notions of ANNs. Also, people who\nonly want to apply the backpropagation algorithm without a detailed and formal explanation\nof it will find this material useful. This work should not be seen as “Nets for dummies”, but of\ncourse it is not a treatise. Much of the formality is skipped for the sake of simplicity. Detailed\nexplanations and demonstrations can be found in the referred readings. The included exercises\ncomplement the understanding of the theory. The on-line resources are highly recommended\nfor extending this brief induction.",
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            "title": "Artificial Neural Networks and Grey Systems for\nthe Prediction of Slope Stability",
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            "abstractNote": "The interactions between factors that affect slope instability are complex, multi-factorial,\nand often difficult to describe mathematically, imposing a challenge for prediction using traditional\nmethods. The power of the ANN and Grey Systems approaches lies in employing the behaviour of\nthe system rather than knowledge of explicit relations. Published data has been used to illustrate the\napplication of these techniques to predicting the state of slope stability. This has been developed into\na tool for analysing and predicting future ground movement based on geotechnical properties and\nhistorical behaviour.",
            "publicationTitle": "Natural Hazards",
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            "title": "A study of slope stability prediction\nusing neural networks",
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            "abstractNote": "The determination of the non-linear behaviour of multivariate dynamic systems\noften presents a challenging and demanding problem. Slope stability estimation is an engineering\nproblem that involves several parameters. The impact of these parameters on the\nstability of slopes is investigated through the use of computational tools called neural networks.\nA number of networks of threshold logic unit were tested, with adjustable weights. The\ncomputational method for the training process was a back-propagation learning algorithm. In\nthis paper, the input data for slope stability estimation consist of values of geotechnical and\ngeometrical input parameters. As an output, the network estimates the factor of safety (FS)\nthat can be modelled as a function approximation problem, or the stability status (S) that can\nbe modelled either as a function approximation problem or as a classification model. The\nperformance of the network is measured and the results are compared to those obtained by\nmeans of standard analytical methods. Furthermore, the relative importance of the parameters\nis studied using the method of the partitioning of weights and compared to the results obtained\nthrough the use of Index Information Theory.",
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            "abstractNote": "Location of the critical shear plane (CSP) plays a major role in determining landslide-initiation thresholds.\nDepth to the CSP increases as the soil shear strength increases. Tree roots provide a significant strength contribution to\nsoil shear strength. Our objective is to understand how vegetation can be used to increase landslide-initiation thresholds\nby changing the location of the CSP. This will enable us to select and compare combinations of plant species and densities\nto suit any given situation to increase landslide-initiation thresholds and improve slope stability. The CSP location\nis estimated incorporating available root cross-sectional area – root depth data in the stability analysis in terms of energy.\nThe energy approach has been developed to take into account the contribution of the roots to soil strength. Generalization\nof the original energy approach is required to enable its use outside our study areas. Once depth to the CSP\nis found, the time for the wetting front to reach it is found using a soil-water infiltration model. The composite model\ndescribed may be used as a simple tool to choose the most appropriate plant density to maximize the stability of a\ngiven hillslope. A worked example of the model demonstrates how the approximate thresholds for different hillslopes\nwith known plant densities under different climatic conditions are estimated.",
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